pink_noise


pink_noise, a FORTRAN90 code which can generate random values taken from an approximate pink noise signal obeying a 1/f power law.

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Languages:

pink_noise is available in a C version and a C++ version and a Fortran90 version and a MATLAB version and an Octave version and a Python version.

Related Data and Programs:

colored_noise, a FORTRAN90 code which generates samples of noise obeying a 1/f^alpha power law.

CORRELATION, a FORTRAN90 code which contains examples of statistical correlation functions.

NORMAL, a FORTRAN90 code which computes elements of a sequence of pseudorandom normally distributed values.

pink_noise_test

SDE, a FORTRAN90 code which illustrates the properties of stochastic differential equations, and common algorithms for their analysis, by Desmond Higham;

STOCHASTIC_RK, a FORTRAN90 code which applies a Runge-Kutta scheme to a stochastic differential equation.

UNIFORM, a FORTRAN90 code which computes elements of a uniform pseudorandom sequence.

Reference:

  1. Martin Gardner,
    White and brown music, fractal curves and one-over-f fluctuations,
    Scientific American,
    Volume 238, Number 4, April 1978, pages 16-32.
  2. Jeremy Kasdin,
    Discrete Simulation of Colored Noise and Stochastic Processes and 1/f^a Power Law Noise Generation,
    Proceedings of the IEEE,
    Volume 83, Number 5, 1995, pages 802-827.
  3. Edoardo Milotti,
    1/f noise: a pedagogical review,
    arXiv:physics/0204033.
  4. Sophocles Orfanidis,
    Introduction to Signal Processing,
    Prentice-Hall, 1995,
    ISBN: 0-13-209172-0,
    LC: TK5102.5.O246.
  5. William Press,
    Flicker Noises in Astronomy and Elsewhere,
    Comments on Astrophysics,
    Volume 7, Number 4, 1978, pages 103-119.
  6. Miroslav Stoyanov, Max Gunzburger, John Burkardt,
    Pink Noise, 1/f^alpha Noise, and Their Effect on Solutions of Differential Equations,
    International Journal for Uncertainty Quantification,
    Volume 1, Number 3, pages 257-278, 2011.

Source Code:


Last revised on 06 August 2020.